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Mini-talks: The Machine Intelligence Landscape: A Venture Capital Perspective by David Beyer. The future of global, trustless transactions on the largest graph: blockchain by Olaf Carlson-Wee. Algorithms for Anti-Money Laundering by Richard Minerich.

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Operations & Infrastructure

Mini-talks: The Machine Intelligence Landscape: A Venture Capital Perspective by David Beyer. The future of global, trustless transactions on the largest graph: blockchain by Olaf Carlson-Wee. Algorithms for Anti-Money Laundering by Richard Minerich.

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Enterprise Architecture

Mini-talks: The Machine Intelligence Landscape: A Venture Capital Perspective by David Beyer. The future of global, trustless transactions on the largest graph: blockchain by Olaf Carlson-Wee. Algorithms for Anti-Money Laundering by Richard Minerich.

Hive Content on InfoQ

Big Data as a Service, an Interview with Google's William Vambenepe
by
Chris Swan
Posted on
Jul 06, 2015
Many of the Big Data technologies in common use originated from Google and have become popular open source platforms, but now Google is bringing an increasing range of big data services to market as part of its Google Cloud Platform. InfoQ caught up with Google's William Vambenepe, who's lead product manager for Big Data services to ask him about the shift towards service based consumption.

Interview with Alex Holmes, author of “Hadoop in Practice. Second Edition”
by
Boris Lublinsky
Posted on
Nov 20, 2014
The new “Hadoop in Practice. Second Edition” book by Alex Holmes provides a deep insight into Hadoop ecosystem covering a wide spectrum of topics such as data organization, layouts and serialization, data processing, including MapReduce and big data patterns, special structures along with their usage to simplify big data processing, and SQL on Hadoop data.

InfoQ eMag: Hadoop
Apache Hadoop is proving useful in deriving insights out of large amounts of data, and is seeing rapid improvements. Hadoop 2 now goes beyond Map-Reduce; it is more modular, pluggable and flexible and it fits a variety of use cases better. We explore this as well as some tools that can help utilize Hadoop better.
View book details

Optimizing for Big Data at Facebook
by
Ashish Thusoo
Posted on
Apr 17, 2012
Hive co-creator Ashish Thusoo describes the Big Data challenges Facebook faced and presents solutions in 2 areas: Reduction in the data footprint and CPU utilization. Generating 300 to 400 terabytes per day, they store RC files as blocks, but store as columns within a block to get better compression. He also talks about the current Big Data ecosystem and trends for companies going forward.